What data for this category looks like
This category of data comes from daily outputs of enterprise metrology rooms and CNAS system laboratories. It includes documents such as gauge ledgers, calibration plans, calibration certificates, interim verification records, reference material ledgers, and deviation disposition forms. Data sources cover metrology management systems, external calibration institution certificates, LIMS systems, and environmental monitoring equipment. Update cycles are triggered by calibration periods, single test results, or abnormal situations. Fields include gauge unique IDs, calibration dates, measurement uncertainties, traceability standard instrument numbers, and usage statuses. Units involve professional metrology units such as millimeters, newtons, and degrees Celsius.
Constraints imposed on knowledge base retrieval and recall by these characteristics
The traceability association attributes of this category of data require retrieval to accurately match association relationships between multiple documents. Matching only a single keyword cannot meet requirements. Mixed document formats of structured ledgers and unstructured certificates require retrieval to support multi-type content recall. Non-fixed update frequencies require the retrieval system to support incremental indexing, to avoid resource consumption from full reconstruction. Semantic matching requirements for professional fields such as measurement uncertainty raise higher standards for retrieval semantic consistency. In traceability scenarios, multiple associated documents must be recalled simultaneously, which imposes clear constraints on the number of results returned per single retrieval.
How to configure the system
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
similarity | 0.75–0.85 | Match professional metrology terms and associated fields, filter low-relevance results |
limit | Top 10 entries | Cover multi-document associations required for traceability, control single-round retrieval context length |
searchMode | embedding | Adapt to matching professional semantic fields such as measurement uncertainty and traceability numbers |
usingReRank | Enabled | Reorder recall results by professional relevance, improve ranking of core documents such as calibration certificates |
datasetSearchUsingExtensionQuery | Enabled | Recall extended associated fields in gauge ledgers and calibration certificates |
collectionIds | Exclusive dataset IDs for measuring instruments and calibration certificates | Limit retrieval scope to avoid mixing irrelevant documents from other categories |
Note: This configuration applies to FastGPT v4.17.0
Three common misconfigurations
- Symptom: Knowledge base search returns no results, with an empty result list displayed in the interface. Cause: After upgrading FastGPT from v4.9 to v4.10, the original dataset association configuration was reset, and
collectionIdswas not re-specified as the metrology instrument-related dataset. - Symptom: Retrieval reports the error
invalid configuration parameter name "hnsw.max_scan_tuples". Cause: An officially unsupported index parameter was used, and FastGPT-specified configuration items were not utilized. - Symptom: Recall results do not include the measurement uncertainty field from calibration certificates. Cause:
datasetSearchUsingExtensionQuerywas not enabled, and only basic text content was recalled.
How to confirm the configuration is properly set
- Access the FastGPT application configuration page, confirm that exclusive datasets for measuring instruments and calibration certificates have been associated.
- Enter a professional search term, such as "outside micrometer calibrated in March 2024", verify that recall results include the corresponding gauge ledger and calibration certificate.
- Check application runtime logs, confirm that there are no errors of the type
invalid configuration parameter name. - Search for traceability-related keywords, verify that recall results include multiple associated documents that meet traceability requirements.
The values provided here are common starting points and should be evaluated against the reader's own samples.